The Learning Network

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Although artificial intelligence technology has been around for some time, current advancements in this space warrant more ethical approaches for developing and deploying AI systems to benefit a large portion of society. Artificial intelligence, generative AI in particular,has already shown immense potential to augment human capabilities. This potential, however, doesn’t seem to be evenly distributed. What’s worse, risks such as social and economic disparities are exacerbated by the uneven distribution of artificial intelligence, and are concentrated in specific regions based on demographic characteristics. It’s imperative to strive toward building a framework of transparency, fairness, and accountability around artificial intelligence on a global scale in order to mitigate this problem.

Owing to the accelerated advancement in the field of generative AI technologies, it’s important to address misconceptions about what generative AI tools can and cannot do in order to maximize the benefits and minimize potential harms. In this “Ask me Anything” session, Amanda demystifies some of the most commonly held misconceptions about generative AI via discussions of real-world use cases. While responding to specific questions, Amanda highlights areas in which generative AI seems to thrive, while she also identifies notable shortcomings of the technology by drawing from her diverse and extensive experience as a digital transformation expert and a sought-after advisor to leading organizations in artificial intelligence and machine learning technologies.

Following the abrupt uptick of generative AI innovation in the past couple of years, organizations have ramped up research and development efforts to meaningfully explore the value of integrating generative AI into organizational systems, with a particular interest in achieving operational hyper-efficiency. This effort requires a deep understanding of the steps towards operationalizing generative AI—from development to adoption to deployment—involving benefits and risks that must be carefully considered to augment performance and financial gains. 

The digital and sustainability paths, previously considered to be parallel, are now highly intersecting and reinforcing each other, pointing towards a symbiotic relationship between technological advancement and environmental values. Showcasing this relationship, digital technologies are expected to contribute more than one-fifth, and up to one-third, of the GHG emissions reduction required by the Paris Agreement by 2030, illustrating their importance to sustainability transformation. As such, it’s important to understand the main drivers of this shift because of the implications this shift has on the global business landscape, including the demand for businesses to prioritize integrating digital innovation with sustainable practices. With the eco-digital economy including benefits that extend well beyond improvement in core business activities, it’s imperative for leaders to have a vision for digital transformation at their organizations going forward with a focus on harnessing the opportunities created by the emerging eco-digital economy including digital strategy, cybersecurity, sustainability, and more. 

Understanding AI product management has become more crucial than ever, particularly in light of recent advancements in the spaces of AI and Machine Learning technologies punctuated by the proliferation of generative AI models. Considering the speed with which AI is becoming pervasive, having a strong grasp of AI concepts and frameworks is critical especially for aspiring AI product managers without significant technical (e.g., coding) background. This opens up exciting opportunities for non-technical product managers whilst making the field of AI product management more accessible, which is a precursor for innovating and building groundbreaking products that address complex, real-world challenges through leveraging cutting-edge technology. Product managers may have to unlearn things they learned in the past. It requires a new mindset.

Work, the workforce, and the workplace is subjected to constant disruption primarily as a result of advancements in technology. Weather it is the impact of robotization to manual work or the disruption of knowledge-based work as a result of software-enabled innovation, career values are being redefined to accommodate for the evolving nature of work. This begs many questions, most importantly, the short and long-term implications of such advancements in technology to the concept of work as we ‘used’ to know it and by extension the values we associate with our careers. Using a novel data of resumes from 16 million individuals in the United States, this research study shades light on the existential question of technological disruption to the labor market and impact on career values.

The following insights are derived from a recent Insights from the Field event featuring Chad Sanderson, covering the topic of Data Contracts for achieving high-quality data for Artificial Intelligence (AI). Overview Chad began this session by demystifying some hyperbolic claims in the world of Artificial Intelligence (AI), including the idea that AI models could replace […]

The following insights are derived from a recent Assembly talk featuring Hywel Benbow, regarding applying data analytics to enhance the performance of educational institutions. We presented a few question to Hywel during this talk, and what follows is a summary of his responses. Could you speak to some overarching and generalizable ways educational organizations could […]

Since the launch of ChatGPT, GenAI has taken center stage, prompting business leaders to explore its potential for creating value. In a recent stimulating discussion featuring Bratin Saha, Iavor Bojinov, and Edward McFowland III, the conversation delved deep into the radical potential of GenAI and its seismic impact on businesses.